Background: The American College of Obstetricians and Gynecologists released Committee Opinion No. 736: Optimizing Postpartum Care (CO No. 736) to address severe maternal morbidity and mortality in the United States by outlining recommendations for care in the critical time following birth. This study aimed to evaluate implementation of and barriers to the recommendations of CO No. 736 among obstetricians in south Louisiana.Methods: A survey to general obstetric providers assessed opinions on the CO No. 736 recommendations, implementation of these recommendations, and barriers to implementation. Fisher exact test was used to compare distributions between resident and attending groups. Qualitative, free-text responses about barriers to implementation were organized by common themes and categorized into systemic and patient factors.Results: Of 124 survey responses, 59.7% of respondents reported that they had read CO No. 736. Of the respondents who had read the document, 86.5% believed it was important to implement these recommendations, but only 50.0% had established the recommendations in their practices. Overall, fewer than half (46.8%) of respondents reported actively implementing the recommendation to make contact with postpartum patients at 3 weeks or sooner, but 86.3% reported having comprehensive clinic visits within 12 weeks of delivery. Commonly identified systemic barriers to implementation included the 3-week contact not being common practice, overbooked schedules, and unclear provider expectations. Commonly identified patient factor barriers to implementation included childcare or transportation and no-shows at postpartum appointments.Conclusion: Both resident and attending obstetricians in South Louisiana believe that the CO No. 736 recommendations are important but reported lacking the ability to implement them into clinical practice. CO No. 736 contains 10 recommendations that focus on the continuum of care during pregnancy and the postpartum period and address the timing and content of provider assessments, reproductive life planning, and the management of medical conditions. With growing evidence for improved outcomes based on optimization of postpartum care,5 CO No. 736 was developed to support the implementation of these recommendations into clinical practice. The opinion, developed by the ACOG Presidential Task Force on Redefining the Postpartum Visit and the Committee on Obstetric Practice,1 has been endorsed by key stakeholders in the field of maternal health.In May 2018, the American College of Obstetricians and Gynecologists (ACOG) released Committee Opinion No. 736: Optimizing Postpartum Care (CO No. 736) to address severe maternal morbidity and mortality in the United States by outlining recommendations for care during the critical time following birth.6 We purposely focused on practices caring for an underserved population at risk for higher rates of maternal morbidity and mortality. The primary aim of our study was to survey if obstetricians in south Louisiana are applying or attempting to apply the CO No. 736 recommendations in their office practices. A secondary aim of our study was to identify perceived barriers to implementation of the CO No. 736 recommendations. We were specifically interested in the frequency of postpartum follow-up among providers, considering that CO No. 736 recommends a patient encounter within 3 weeks of delivery. We posited that the majority of obstetrics and gynecology (OB/GYN) providers surveyed were not implementing contact within 3 weeks postpartum but were implementing the recommendation for a comprehensive visit within 12 weeks.The goal of this study was to understand postpartum care practices in south Louisiana, a state with maternal mortality rates higher than the national average.The study team disseminated a 17-item survey  in perso8 REDCap is a secure, web-based software platform designed to support data capture for research studies, providing (1) an intuitive interface for validated data capture; (2) audit trails for tracking data manipulation and export procedures; (3) automated export procedures for data downloads to common statistical packages; and (4) procedures for data integration and interoperability with external sources.Surveys were anonymous, and no identifying information was collected from respondents. In New Orleans, surveying took place from June through September 2019 and was conducted in person at OB/GYN Grand Rounds, department meetings, and resident didactics sessions. In Baton Rouge, surveying took place from October through November 2020. Surveying was conducted in person in the physicians’ lounge, but the majority of the surveys at all sites were collected electronically using a REDCap (Vanderbilt University) survey link. Study data collected on paper were transcribed to REDCap for data aggregation. Study data were collected and managed using REDCap electronic data capture tools.1 Level of training, location of practice, and knowledge of CO No. 736 were assessed in survey questions 1 through 3. All survey participants answered 11 questions (questions 1 through 3 and 10 through 17), but only participants who responded “yes” to having previously read CO No. 736 answered 6 of the questions (questions 4 through 9). Responses were 5-point Likert scales. A blank space after each Likert scale question was provided to allow respondents to voluntarily describe barriers that they faced in implementing that specific recommendation. Question 17 invited free-text responses regarding implementation of the recommendations.The 17 questions on the survey  were infP values <0.05 were considered statistically significant.Responses were grouped into 2 categories: low implementation of recommendations  and high implementation of recommendations . To compare the distribution of answers among resident and attending physicians, Fisher exact test was used to compare the resident and attending physician groups to test differences in training level on implementation of recommendations. This approach avoided the low response counts if Likert score values were tested individually, which would cause the test to behave poorly. Researchers coded qualitative responses based on common themes that fell into 2 categories—systemic factors and patient factors—using a general inductive approach after all results were collected. These qualitative responses are also presented by training level. Because our study was exploratory in nature and without a specific hypothesis to test or preliminary data, a power analysis was not conducted.A total of 124 surveys were collected from resident (n=44) and attending (n=80) OB/GYN providers from an available physician pool of 225, for an overall response rate of 55.1%. The response rates for New Orleans physicians were 52.9% (n=68) and 46.2% (n=78) for residents and attendings, respectively. The response rates for Baton Rouge physicians were 50.0% (n=16) for residents and 69.8% (n=63) for attendings, respectively.In addition to respondent training level and geographic location, P=0.001). Both groups reported high implementation levels for the majority of the recommendations.A composite score (0-7) was calculated for each survey respondent based on their self-reported high or low implementation of each of the 7 primary recommendations of CO No. 736: contact within 3 weeks of giving birth; comprehensive postpartum visit no later than 12 weeks after birth; discussion of postpartum care plan; discussion of reproductive life plans; counseling about future cardiovascular disease risk; counseling for chronic medical conditions; and follow-up visit after miscarriage, stillbirth, or neonatal death. The mean composite score for attending OB/GYN providers was 6.0 ± 1.1, which was slightly higher than the OB/GYN resident mean score of 5.2 ± 1.2 (P=0.04). Both residents (72.7%) and attendings (93.8%) reported high implementation of the recommendation for a comprehensive postpartum visit within 12 weeks following delivery; however, implementation among attendings was significantly higher than among residents (P=0.002).The lowest compliance rate was for the recommendation that patients have contact with a maternal care provider within 3 weeks postpartum. Only 34.1% of OB/GYN residents reported “usually”/“always” having contact with patients within 3 weeks of delivery vs 53.8% of OB/GYN attendings, a statistically significant difference (P=0.013). For the recommendations to discuss reproductive life plans and to counsel patients with pregnancies complicated by diabetes or hypertensive disorders that these disorders are associated with a higher lifetime risk of cardiovascular diseases, high implementation was reported overall by 86.3% and 87.7% of respondents, respectively, with no differences seen between residents and attendings in the reported rates of implementation.The recommendation with the second lowest implementation rate was providing anticipatory guidance and developing a postpartum care plan that addresses infant feeding, “baby blues,” postpartum emotional health, and the challenges of parenting and postpartum recovery from birth. Overall, 71.0% of respondents reported high implementation of this recommendation, with a significantly lower implementation reported by residents (56.8%) vs attendings (78.8%) (P=1) and follow-up visits after a miscarriage, stillbirth, or neonatal death .The 2 recommendations for which respondents reported the greatest level of high implementation were counseling patients with chronic medical conditions about the importance of timely follow-up  were asked additional questions about implementing the recommendations in their clinical practice . OverallFree-text qualitative data were collected for respondents who answered anything except a score of 5  on the 5-point Likert scale for questions 10 through 16. Comments about the barriers to contacting patients within 3 weeks of delivery (the recommendation with the lowest implementation) were organized by theme—systemic factors or patient factors—and reported as resident and attending physician responses . Both reComments for barriers to implementing a comprehensive postpartum visit by 12 weeks were also organized by theme—systemic factors or patient factors—and reported as resident and attending physician responses . MirroriFor both the 3-week contact and the comprehensive visit by 12 weeks, attendings cited problems with insurance coverage for patients and reimbursement for physicians as barriers to implementation more frequently than residents.Among the surveyed population representing a diverse snapshot of OB/GYN providers in the Baton Rouge and New Orleans areas, our survey study revealed that only 59.7% of the respondents had read the ACOG Committee Opinion No. 736: Optimizing Postpartum Care. Regardless of whether respondents had or had not read CO No. 736, our study revealed that the majority of respondents were implementing the opinion recommendations to a limited degree. We found that the postpartum care recommendations were implemented less frequently among residents compared to attending OB/GYN providers.9 Consequently, the postpartum period must be part of any strategy to reduce maternal morbidity and mortality. Particularly relevant to the surveyed population, Louisiana has one of the highest maternal mortality rates in the country, and the mortality rate is increasing at a higher rate than the rest of the United States.9 Postpartum care practices contribute to maternal morbidity and mortality,1 making this phase of care an important topic for all providers. Credit should be given to CO No. 736 for recommending postpartum care as an ongoing process rather than an isolated visit at 6 to 12 weeks after delivery. Ultimately, full implementation of these recommendations to change the scope of postpartum care must be facilitated by reimbursement policy.Our study provides important insight from OB/GYN providers into feelings about and barriers to implementation of the ACOG postpartum care optimization recommendations. Implementation of these recommendations deserves thoughtful consideration as more than half of pregnancy-related deaths occur after delivery.Free-text responses provided insight into perceived barriers that may be limiting implementation of the CO No. 736 recommendations, and both resident and attending OB/GYN providers provided similar insights. The most commonly reported barriers to implementation of making contact by 3 weeks postpartum and completing a comprehensive visit by 12 weeks were consistent among residents and attendings and included overbooked schedules, unclear roles of providers for these visits, patient no-shows, and patient transportation or childcare. Respondent suggestions for alleviating these barriers included using midlevel providers to schedule appointments, contacting patients during the 3-week postpartum window, and assisting with patient reminders for postpartum visits.Moreover, those who had read CO No. 736 reported feeling that their facility had not implemented the recommendations despite their opinion that the recommendations are important. Institutional support, both endorsement and allocation of resources, for piloting the 3-week postpartum contact is an opportunity to help providers implement this recommendation into their practices.1 with lower attendance rates for patient populations with limited resources.10 At the academic medical centers where the surveys for this study were disseminated, attendance rates for the comprehensive postpartum clinic visit 6 to 12 weeks after delivery were approximately 50% in Baton Rouge and 42% in New Orleans in 2021, both below the national average.An additional common barrier to postpartum care recommendations that deserves discussion is the report of no-shows to postpartum appointments. Approximately 60% of patients attend a postpartum visit in the United States,Incorporation of additional visits or contacts into the standard postpartum visit schedule would require considerable effort to support patient compliance as attendance at the standard 6- to 12-week postpartum visit is already lacking. However, increasing patient contact in the postpartum period stands as a potentially high-reward opportunity among the obstetric population who experience both limited postpartum follow-up and high rates of pregnancy-related morbidity in the postpartum period.Our study has strengths, limitations, and opportunities for future work. A strength of our study is sampling among multiple academic centers (n=3) in 2 regions in south Louisiana. Another strength is receipt of physician responses across several different practice groups and settings, particularly among attending physicians in Baton Rouge and resident physicians in New Orleans. A limitation is the low response rate among all the eligible providers in the regions sampled. Another limitation is the inability to distinguish academic vs private practice responses because of the anonymity of the survey. Regarding future opportunities with this work, many barriers reported are organizational barriers; therefore, future studies should focus on investigating specific organizational opportunities to implementation of postpartum care. Expansion of this work will include statewide dissemination to obstetric providers to increase responses and gain insight outside of urban settings. Future retrospective studies could also be performed that use actual occurrence rates of postpartum care practices rather than provider self-reported rates. Suggestions to begin working toward the implementation of the optimal postpartum care recommendations include supporting obstetric practices in implementing the recommendations from CO No. 736, emphasizing postpartum care at prenatal visits, using support staff to remind patients of their appointments, using midlevel providers to assist with schedule burden, emphasizing postpartum visits in discharge planning, scheduling postpartum telehealth visits and comprehensive visits at discharge, and sending text or email reminders. Advocacy for support of statewide insurance coverage for the 3-week visit could also reduce barriers to implementing that visit. Providing childcare services in clinic and allowing children to accompany the patient for the first postpartum visit could also potentially assist in boosting attendance rates. Looking ahead, we are conducting a quality improvement project in which these insights will be applied to a 3-week postpartum telehealth visit with patients in an academic resident clinic.Our survey results show that the ACOG Committee Opinion No. 736: Optimizing Postpartum Care recommendations are being implemented intermittently by both resident and attending OB/GYN providers in South Louisiana. The barriers are several and vary depending on the provider and training level. This work should serve as a reminder of the importance of postpartum comprehensive care in reducing maternal morbidity and mortality in the state of Louisiana. We also hope that the findings from this study serve as a platform to advocate for the reduction of financial barriers across the state to allow patients to access this recommended model of care.


Esophageal cancer (ESCA) is a common gastrointestinal tumor, and China is one of the regions with a high incidence. Tumor immune-related cells play important roles in the tumorigenesis and development of ESCA. However, the role of tumor immune-related genes in the development of ESCA has not been established.  In this study, weighted gene coexpression network analysis (WGCNA) was used to analyze ESCA gene expression using data from The Cancer Genome Atlas (TCGA) database. Gene expression was associated with clinical traits, and modules related to CD8+T cells, dendritic cells, and regulatory T cells (Tregs) were obtained. P < 0.05). The risk assessment analysis also showed that tumor stage was positively correlated with tumor risk in ESCA (P < 0.05). Therefore, more than 50 pairs of tumor tissues from the T1–T3 stages with different degrees of differentiation and paracancerous tissues were selected to confirm the expression of the three genes using RT-qPCR and immunofluorescence (IF). The infiltration of CD8+ T cells in tumor tissues was lower than that in normal tissues. According to the RT-qPCR, the expressions of IL17 C, TNFSF15, and MIA in moderately and poorly differentiated tissues were significantly higher than those in normal tissues (P < 0.05). In contrast, their expressions were decreased in high differentiated tissues (P < 0.05). Furthermore, IL17C, TNFSF15, and MIA were all positively correlated with immune checkpoint PD-1; TNFSF15 and MIA were also positively correlated with CTLA4, TIGIT, and CD96.  The GO analysis showed that inflammatory chemotaxis networks were activated by cell chemotaxis, chemokine activity, and chemokine binding receptor. Three hub genes  related to tumor immunity and metastasis were identified by WGCNA, and the abnormal expression of each hub gene in ESCA has a poor prognosis, especially in patients with high expression ( In summary, IL17C, TNFSF15, and MIA may act as biomarkers for prognosis in moderately and poorly differentiated ESCAs, and they may be used as predictive genes of immunotherapy associated with CD8+ T cell and Tregs invasion in ESCAs. Esophageal cancer (ESCA) is one of the most aggressive tumors and the sixth leading cause of cancer-related deaths globally. In developing countries, ESCA ranks eighth in incidence and fifth in mortality . It is e+ FoxP3-T cells (TCONV) are capable of inhibiting antitumor immune responses, promoting tumorigenesis, and accelerating metastasis [+ T cells in ESCA and provide a basis for ESCA treatment.Tumor-infiltrating immunocytes have been implicated during different stages of tumorigenesis and development . Activattastasis –12. Tumohttps://www.bioconductor.org). At the same time, we converted RNA-seq-FPKM-count to RNA-seq-TPM-count. Finally, only 1078 immune-related genes downloaded from the ImmPort database (https://www.immport.org/) were selected for WGCNA.We obtained RNA expression and clinical data of ESCA from TCGA, including those for 165 tumor specimens and 11 normal specimens. First of all, we used the “org.Hs.eg.db” package in R language to convert the “Ensembl id” into a gene symbol . It can accurately estimate the immune components of the tumor biopsies . Therefohttps://software.broadinstitute.org/gsea/msigdb/index.jsp) were enriched and analyzed using the GSEA_4.1.0. The immune-related pathways were also enriched.According to the median of gene expression, we divided the patients into two groups as follows: high and low expression groups. The hallmark, c2, c5, and c7 gene sets downloaded from the Molecular Signatures Database (R2 = 0.85) to construct the weighted adjacency matrix. Furthermore, the weighted adjacency matrix was transformed into a topological overlap matrix (TOM) to estimate the connectivity of genes in the network generation. Based on the differential detection of TOM, we chose a cutting height of 0.25 and a minimum module size of 30 and divided the gene into nine different modules.The R software package “WGCNA” is used to construct a coexpression network with the expression values of 1078 genes to generate sample clusters and detect outliers . “FlashCP < 0.05, an individual module was considered to be significantly related to immune cells. We selected the immune cell subtypes of interest and the module with the highest correlation coefficient and formed the hub module with them. In addition, we calculated the correlation between the genes and clinical features (cor. gene significance) and the correlation between the genes and MEs (cor. Gene module membership) to screen key genes in the hub module.Module eigengenes (MEs) are defined as the principal components of each module. To determine the significance of the modules, we calculated the correlation between the MEs and the level of immune cell infiltration in the tumor tissue using the Pearson test. At We performed multivariate Cox proportional hazards regression analysis to determine the association of clinical parameters, including age, gender, tumor stage, and smoking, with a prognostic assessment of ESCA. Risk scores were calculated using the following formula:In addition, the correlation between three genes and immune cells was, respectively, analyzed by the Pearson correlation coefficient. Furthermore, the same correlation coefficient was used to analyze the correlation between three hub genes and immune checkpoints. Pearson correlation coefficient was calculated using the following formula:https://kmplot.com/analysis/) to analyze the correlation between the panoncogene (hub gene) mutation group and the normal control group in patients with ESCA. In addition, we obtained the mutation rate of hub genes from the cBioportal database .Genes related to inflammation and metabolism were selected as hub genes for the key genes. Next, we used Kaplan–Meier plots  and eosin (Solarbio) and partly with immunofluorescence, incubated with CD8 (Bioss) antibodies, and then examined under a fluorescent microscope.We fixed the collected ESCA tissue as well as paracancerous tissue in 4% paraformaldehyde (PFA) followed by paraffin embedding. The wax blocks were cut into 5 #K1622, Thermo Fisher Science). The cDNAs were amplified by real-time quantitative PCR (RT-qPCR) with specific primers  was used as the luminescent substrate. Finally, we analyzed the melting curve, and the expression of the hub gene was normalized with β-actin.The tissues were lysed with Trizol reagent (TaKaRa), and the total RNA was extracted. The concentrations of total RNA were detected using a NanoDrop 2000 C spectrophotometer . The total RNA was reverse-transcribed into cDNA by Revertaid First Strand cDNA synthesis reagent , while the infiltration of naïve B-cells in the tumor was higher than that in the normal group (P < 0.05)  . As showP < 0.05); the downregulated IL6 deprivation pathway genes were enriched in tumor tissues (P < 0.05) (+FoxP3-T (TCONV) cell characteristic genes that promote tumor migration and metastasis were enriched in tumors, while nature Treg cell characteristic genes were downregulated  , CD4+Foxegulated , and melegulated .We obtained 1100 gene expression matrices and clinical information related to adaptive immunity in ESCA tissues from the TCGA database, excluding one outlier sample, and constructed a hierarchical clustering tree  for the + T cells, naïve B cells, plasma cells, memory resting CD4 T cells, and regulatory T cells. We selected two modules with the highest correlation in the CD8+ T cells, as denoted by the ME-turquoise  and ME-blue rows . At the same time, we selected two modules with the highest correlation in the regulatory T cells, as denoted by the ME-turquoise  and ME-brown  rows  rows . The bub05) rows .+ memory-activated T cells. In addition, TNFSF15 and MIA expression were positively associated with Tregs and CD4+ memory resting T cells, respectively (P < 0.05) (P < 0.05), and they all presented several alterations including amplification and deletion in patients with ESCA  . In addiith ESCA .P < 0.05). The overall survival duration of patients with IL17C gene abnormalities was shorter, even less than one year (P < 0.05). Moreover, we also analyzed the relationship between the expression of the three genes and prognostic survival using the TCGA database. The results showed that patients with low expression of IL17C, TNFSF15, or MIA lived longer than those patients with high expression of one of them (P < 0.05)  of the patients with the three abnormal hub genes was analyzed using the cBioPortal database. The cBioPortal database contains 2201 clinical samples from eight ESCA-related research websites. As shown in  < 0.05) .P < 0.05). Therefore, tissues from patients with stage-T1 to T4 ESCA who were only treated with surgery were selected to verify these candidate genes. The tumor stage was determined based on the results of pathological HE staining   ; IL17C expression was positively correlated with PD-1 (P < 0.05)  .+FoxP3-T (TCONV) cell characteristic genes that promote tumor migration and metastasis were enriched in tumors, while nature Treg cell characteristic genes were downregulated. Therefore, to determine the characteristics of adaptive immunity-related genes in ESCA, we performed RNA-seq analysis of the ESCA samples and compared the expressions of adaptive immunity-related genes with that of normal tissues, and three modules related to CD8 T cells and Tregs were obtained.CD8+ T cells play an essential role in effective immune responses. In our study, the infiltration of cytotoxic T cells was decreased in tumor tissues, suggesting that tumor immunity was disregulated. Furthermore, CD4α, which plays an important role under disease conditions, such as cancer and stroke, by maintaining vascular and lymphatic vessel homeostasis [On this basis, IL17C, TNFSF15, and MIA which were related to tumor immunity, invasion, and metastasis were identified. IL17C, an autocrine cytokine, is an important factor in the innate immunity of the epithelium. IL17C may promote or inhibit tumorigenesis by regulating immune cell function [eostasis –21. In oeostasis . But in Furthermore, the analysis of immunocyte infiltration in ESCA suggested that CD8+ T cells were significantly lower than that in paracancerous tissue, and we used IF to confirm that CD8+ T cells were reduced in ESCA tissues. PD-1, CTLA4, CD96, and TIGIT are associated with each other in tumor immunity, which are candidates for immunotherapy –26. IL17However, there were some limitations in our study, such as the sample size limiting the accuracy of the analysis and the experimental results. Furthermore, more time was needed to review patients with special gene phenotypes and evaluate their prognosis. Finally, the specific mechanisms underlying the actions of these alteration genes in ESCA need to be elucidated in future research.In summary, we used multiple biological information analyses and experiments involving clinical samples to identify potential biomarkers of ESCA. Three hub genes were identified to be abnormally expressed in tumors, and they affected the prognosis of patients with ESCA. The immune cell function regulating IL17C, TNFSF15, and MIA have been identified as potential biomarkers for the evaluation of ESCA diagnosis and prognosis, which may also be predictors of immunotherapy.In this study, CD8+ T cells were decreased in tumor tissues which contributed to the immune imbalance of the tumor. WGCNA was used to identify the characteristics of immune-related genes in ESCA. Three modules related to CD8+ T cells and Tregs were identified, and three hub genes related to the survival duration and prognosis of ESCA were obtained, which are IL17C, TNFSF15, and MIA, and they can be used as therapeutic targets for further study and clinical markers to predict the prognosis of patients.


In vitro studies of the affinity of the synthesized compounds to the protein target have been carried out. Based on these ligands, a series of bimodal conjugates with a combination of different mitosis inhibitors and antiandrogenic drugs were synthesized. The cytotoxicity of the compounds obtained in vitro was investigated on three different cell lines. The efficacy of the two obtained conjugates was evaluated in vivo in xenograft models of prostate cancer. These compounds have been shown to be highly effective in inhibiting the growth of PSMA-expressing tumors.Prostate cancer is the second most common cancer among men. We designed and synthesized new ligands targeting prostate-specific membrane antigen and suitable for bimodal conjugates with diagnostic and therapeutic agents.  Prostate cancer (PCa) is currently the second most newly diagnosed cancer in men . CurrentS)-2-(3-((S)-5-amino-1-carboxypentyl)ureido)pentanedioic acid) and DUPA -2,2′-(carbonylbis(azanediyl))dipentanedioic acid) are used as vector fragments in these studies.Another promising approach in modern cancer therapy and diagnosis is the use of a combination of different agents. A number of examples of different combinations of therapeutic or diagnostic agents, are present in the literatures ,10,11. IIn vitro affinity studies of the resulting compounds have confirmed their ability to bind effectively to PSMA. In order to test the possibility of efficiently producing double conjugates, it was decided to synthesize a series of therapeutic conjugates with a combination of antiandrogenic agents and mitosis inhibitors based on the obtained PSMA ligands. The selection of this mix of drugs is based on a number of studies that have already tested such combinations R = 11.05 min.HPLC-MS: target compound content—99.9%, t56H77ClN12O14: m/z calculated for [M+H]+ 1177.5371, found: 1177.5443; m/z calculated for [M+Na]+ 1199.5269, found: 1199.5263.ESI-HRMS: for C6bSynthesis of compound 5b and 7 mL of a mixture of trifluoroacetic acid, triisopropylsilane, water and dichloromethane, 126 mg (80% yield) of compound 6b was isolated individually using reverse phase column chromatography  as a white amorphous powder.From 199 mg (0.129 mmol) of compound 1H NMR  δ, ppm: 12.45 , 9.22 , 8.29 , 8.10 , 7.88–7.96 , 7.75–7.82 , 7.65 , 7.55–7.59 , 7.54 , 7.48 , 7.19–7.25 , 7.09–7.19 , 7.03 , 6.65 , 6.26–6.37 , 4.49–4.43 , 4.28–4.38 , 4.08 , 3.27–3.32 , 3.12–3.21 , 3.05–3.12 , 2.88–3.05 , 2.77–2.85 , 2.73 , 2.61–2.69 , 2.26–2.35 , 2.14–2.26 , 1.85–1.96 , 1.65–1.75 , 1.57–1.65 , 1.45–1.55 , 1.34–1.44 , 1.31 , 1.12–1.29 .13C NMR  δ, ppm: 174.55, 174.26, 173.82, 172.71, 172.07, 171.77, 171.59, 171.24, 171.08, 157.32, 155.91, 138.02, 137.94, 131.55, 131.24, 130.03, 129.72, 129.02, 128.64, 128.09, 127.84, 126.29, 120.14, 119.92, 114.99, 55.00, 52.61, 52.17, 51.73, 51.24, 48.23, 46.74 38.66, 36.87, 35.85, 31.90, 31.17, 30.77, 30.58, 29.97, 29.07, 28.26, 27.59, 26.65, 26.29, 24.72, 24.59, 22.31.20D = −9.0°[α]R = 10.8 min.HPLC-MS: target compound content—99.9%, t56H77BrN12O14: m/z calculated for [M+H]+ 1221.49383, found: 1221.4937.ESI-HRMS: for C6cSynthesis of compound 5c and 11 mL mixture of trifluoroacetic acid, triisopropylsilane, water and dichloromethane, 126 mg (80% yield) of compound 6c was isolated individually using reverse phase column chromatography  as a white amorphous powder.From 282 mg (0.180 mmol) of compound 1H NMR  δ, ppm: 12.56 , 9.22 , 8.29 , 8.10 , 7.89–7.97 , 7.87 , 7.74–7.82 , 7.65 , 7.53–7.60 , 7.25–7.32 , 7.18–7.25 , 7.12–7.18 , 7.03 , 6.60–6.69 , 6.25–6.38 , 4.60–4.53 , 4.26–4.38 , 3.98–4.16 , 3.32 , 3.17 , 3.05–3.13 , 2.88–3.05 , 2.69–2.86 , 2.60–2.69 , 2.30–2.39 , 2.24–2.30 , 2.20 , 1.84–1.96 , 1.56–1.74 , 1.37–1.55 , 1.32 , 1.14–1.29 .13C NMR  δ, ppm: 174.50, 174.21, 173.78, 172.62, 171.73, 171.55, 171.23, 171.07, 167.21, 157.30, 155.89, 137.94, 130.04, 129.78, 129.47, 129.02, 128.09, 127.83, 127.38, 126.29, 114.98, 54.97, 52.56, 52.13, 51.67, 48.23, 38.68, 36.88, 35.85, 31.78, 29.91, 28.26, 27.52, 26.62, 24.71, 22.27.20D = −9.7°[α]R = 10.25 min.HPLC-MS: target compound content—99.0%, t56H78N12O16: m/z calculated for [M+H]+ 1187.57315, found: 1187.572.ESI-HRMS: for C6dSynthesis of compound 5d and 6 mL of a mixture of trifluoroacetic acid, triisopropylsilane, water and dichloromethane, 71 mg (76% yield) of compound 6d was isolated individually using reverse phase column chromatography  as a white amorphous powder.From 119 mg (79.6 µmol) of compound 1H NMR  δ, ppm: 12.55 , 8.30 , 8.17 , 7.89–7.99 , 7.87 , 7.77–7.84 , 7.56–7.68 , 7.22–7.30 , 7.20 , 7.15 , 6.26–6.36 , 4.60–4.53 , 4.39–4.48 , 4.31 , 3.98–4.17 , 3.32 , 3.12–3.25 , 3.07–3.12 , 2.97–3.07 , 2.87–2.97 , 2.73 , 2.59–2.69 , 2.30–2.38 , 2.13–2.30 , 1.85–1.96 , 1.64 , 1.50 , 1.41 , 1.12–1.34 .20D = −7.9°[α]R = 10.7 min.HPLC-MS: target compound content—99.9%, tm/z calculated for [M+H]+ 1171.57824, found: 1171.5782.ESI-HRMS: for C56H78N12O15: 8a–dGeneral procedure for the preparation of monoconjugates 6a–d was dissolved in DMF. Compound 7 (1.2 eq.) and DIPEA (6 eq.) were added to the solution. The reaction mixture was stirred until the reaction was completed (the reaction was monitored using TLC in a system of 10% methanol in dichloromethane + 1% trifluoroacetic acid). The solvent was removed under reduced pressure. The dry residue was precipitated with acetonitrile, then decanted and the precipitate was washed three times with acetonitrile.1 eq. of compound 8aSynthesis of compound 6a, 51 mg (92.9 µmol) of compound 7 in the presence of 81 µL (0.464 mmol) of DIPEA in 10 mL of DMF, 131 mg (85% yield) of compound 8a was obtained as white powder.From 100 mg (77.4 µmol) of compound 1H NMR  δ, ppm: 8.53 , 8.39 , 8.15 , 8.01 , 7.84–7.92 , 7.74 , 7.55–7.64 , 7.47 , 7.23–7.40 , 7.08–7.23 , 6.98–7.08 , 6.65 , 6.28–6.38 , 6.08 , 5.27–5.38 , 4.36–4.52 , 4.24 , 3.95–4.12 , 3.28 , 3.14 , 2.99–3.10 , 2.97 , 2.74–2.93 , 2.58–2.69 , 2.42 , 2.08–2.38 , 1.92–2.01 , 1.89 , 1.78 , 1.54–1.73 , 1.26–1.53 , 1.08–1.26 , 0.84–1.08 .R = 8.26 min.HPLC-MS: target compound content—97%, t8bSynthesis of compound 6b, 40 mg (72.7 µmol) of compound 7 in the presence of 63 µL (0.364 mmol) of DIPEA in 9 mL of DMF, 80 mg (80% yield) of compound 8b was obtained as white powder.From 81 mg (60.6 µmol) of compound 1H NMR  δ, ppm: 8.54 , 8.39 , 8.28–8.34 , 8.15 , 7.97–8.05 , 7.92–7.97 , 7.82–7.92 , 7.74 , 7.61 , 7.41–7.55 , 7.33 , 6.98–7.24 , 6.65 , 6.26–6.36 , 6.08 , 5.32 , 4.33–4.53 , 4.25 , 3.94–4.10 , 3.28 , 2.74–3.22 , 2.58–2.70 , 2.38–2.45 , 2.08–2.38 , 1.83–2.08 , 1.26–1.82 , 1.08–1.26 , 0.84–1.07 .R = 8.40 min.HPLC-MS: target compound content—97%, t8cSynthesis of compound 6c, 16 mg (29.5 µmol) of compound 7 in the presence of 30 µL (0.172 mmol) of DIPEA in 5 mL of DMF, 31 mg (78% yield) of compound 8c was obtained as white powder.From 32 mg (24.6 µmol) of compound R = 4.60 min.HPLC-MS: target compound content—99.9%, t85H111N13O19: m/z calculated for [M+H]+ 1618.8119, found: 1618.82.ESI-HRMS: for C8dSynthesis of compound 6d, 24 mg (44.8 µmol) of compound 7 in the presence of 45 µL (0.261 mmol) of DIPEA in 7 mL of DMF, 53 mg (88% yield) of compound 8d was obtained as white powder.From 48 mg (37.3 µmol) of compound 1H NMR  δ, ppm: 8.54 , 8.39 , 8.22 , 8.05 , 7.81–7.93 , 7.74 , 7.62 , 7.53 , 7.33 , 7.21–7.29 , 7.06–7.21 , 6.31 , 6.08 , 5.32 , 4.50–4.57 , 4.38 , 4.23 , 4.06 , 4.01 , 3.29 , 2.78–3.13 , 2.57–2.68 , 2.43 , 2.15–2.30 , 1.88–1.99 , 1.77 , 1.53–1.69 , 1.30–1.50 , 1.19 , 0.97 .R = 6.89 min.HPLC-MS: target compound content—99.9%, t10a–d conjugates using an azide–alkyne cycloaddition reaction.General procedure for the preparation of bimodal 8a–d (1 eq.) and Docetaxel-alkyne 9 (1.2 eq.) were dissolved in a mixture of DMF and water. The flask was filled with argon, then aqueous solutions of sodium ascorbate (1.2 eq.) and copper sulfate pentahydrate (0.4 eq.) were added to the system. The reaction mixture was stirred for 18 h. Afterwards, EDTA (0.8 eq.) was added and stirred for another three hours with access to oxygen in air. The solvent was removed under reduced pressure, the dry residue was precipitated with acetonitrile and decanted. Then, the product was isolated individually using reverse phase column chromatography using acetonitrile–water mixture as eluent.Monoconjugate 10aSynthesis of compound 8a, 40 mg (44.8 µmol) of Docetaxel-alkyne 9, 9 mg (44.8 µmol) of sodium ascorbate, 4 mg (14.9 µmol) of copper sulfate pentahydrate in 8 mL DMF/water mixture (3/1), followed by addition of 9 mg (29.8 µmol) EDTA was isolated individually using reverse phase column chromatography  85 mg (90% yield) of compound 10a as white powder.From 60 mg (37.3 µmol) of compound 1H NMR  δ, ppm: 8.76 , 8.62 , 8.33 , 7.94 , 7.82 , 7.78 , 7.69 , 7.56–7.66 , 7.21–7.44 , 6.97–7.21 , 6.65 , 6.37 , 5.75 , 5.36 , 5.31–5.34 , 4.98–5.09 , 4.84–4.90 , 4.36–4.52 , 4.19–4.33 , 4.03–4.11 , 3.93–4.03 , 3.14 , 2.97 , 2.77–2.90 , 2.54–2–70 , 2.37–2.46 , 2.30 , 2.20–2.26 , 2.19 , 2.15 , 2.04–2.08 , 1.97–2.02 , 1.72–1.97 , 1.68–1.72  1.66 , 1.54–1.64 , 1.47 , 1.29 , 0.98 , 0.94 .13C NMR  δ, ppm: 209.29, 174.39, 174.05, 173.76, 172.45, 172.18, 171.87, 171.81, 171.57, 171.24, 170.89, 169.66, 169.20, 165.40, 157.34, 155.64, 155.23, 148.53, 145.94, 141.01, 140.76, 140.59, 140.28, 139.83, 137.58, 136.76, 136.10, 134.62, 133.57, 133.35, 133.07, 130.62, 130.28, 129.99, 129.88, 129.58, 128.92, 128.74, 128.64, 128.13, 128.00, 127.39, 127.08, 126.88, 126.38, 126.20, 126.00, 124.92, 122.13, 121.86, 118.22, 114.94, 83.80, 80.22, 78.65, 76.75, 75.03, 74.68, 73.62, 73.24, 71.20, 70.67, 56.96, 56.88, 55.22, 52.86, 52.13, 51.51, 49.49, 46.88, 46.65, 42.84, 37.62, 36.25, 35.68, 34.57, 33.99, 32.62, 31.87, 31.52, 31.18, 30.85, 30.61, 29.75, 28.94, 28.73, 28.03, 27.32, 26.38, 26.21, 24.70, 24.25, 24.09, 22.81, 22.47, 20.76, 20.26, 18.87, 15.92, 13.66, 9.78.R = 9.96 min.HPLC-MS: target compound content—99.9%, t133H169ClN14O32: m/z calculated for [M+H]+ 2510.1716, found: 2510.18.ESI-HRMS: for C10bSynthesis of compound 8b, 26 mg (29 µmol) of Docetaxel-alkyne 9, 6 mg (29 µmol) of sodium ascorbate, 3 mg (9.68 µmol) of copper sulfate pentahydrate in 8 mL DMF/water mixture (3/1), followed by addition of 6 mg (19.4 µmol) EDTA was isolated individually using reverse phase column chromatography  40 mg (65% yield) of compound 10b as white powder.From 40 mg (24.2 µmol) of compound 1H NMR  δ, ppm: 8.73 , 8.60 , 8.26 , 7.94 , 7.78 , 7.66–7.77 , 7.58–7.66 , 7.50 , 7.45 , 7.38 , 7.31 , 7.13–7.22 , 7.00–7.13 , 6.65 , 6.33 , 5.74 , 5.29–5.40 , 4.97–5.10 , 4.87 , 4.40–4.46 , 4.18–4.33 , 3.92–4.12 , 3.06–3.22 , 2.90–3.06 , 2.80–2.88 , 2.66 , 2.58 , 2.42 , 2.26–2.37 , 2.10–2.26 , 1.54–1.92 , 1.47 , 1.33–1.42 , 1.29 , 1.07–1.25 , 0.83–1.05 .R = 10.06 min.HPLC-MS: target compound content—99.9%, t133H169BrN14O32: m/z calculated for [M+H]+ 2554.1211, found: 2554.13.ESI-HRMS: for C10cSynthesis of compound 8c, 10 mg (11.1 µmol) of Docetaxel-alkyne 9, 2.2 mg (11.1 µmol) of sodium ascorbate, 1 mg (3.70 µmol) of copper sulfate pentahydrate in 6.7 mL of DMF/water mixture (3/1), followed by the addition of 2.2 mg (7.41 µmol) EDTA was isolated individually using reverse phase column chromatography  14 mg (77% yield) of compound 10c as white powder.From 15 mg (9.26 µmol) of compound 1H NMR  δ, ppm: 8.82 , 8.69 , 8.49 , 7.87–8.01 , 7.85 , 7.78 , 7.65–7.75 , 7.57–7.65 , 7.34–7.47 , 7.31 , 7.25 , 7.13 , 7.17 , 6.98–7.11 , 6.65 , 6.43 , 5.69–5.79 , 5.29–5.39 , 4.97–5.08 , 4.87 , 4.45–4.57 , 4.40 , 4.15–4.32 , 4.05 , 3.91–4.03 , 3.58–3.60 , 3.15 , 2.89–3.09 , 2.84 , 2.64 , 2.58 , 2.42 , 2.30 , 2.10–2.26 , 2.03–2.10 , 1.97 , 1.72–1.93 , 1.69 , 1.66 , 1.58 , 1.61 , 1.47 , 1.31–1.41 , 1.29 , 1.19 , 1.08 , 0.83–1.06 .R = 8.81 min.HPLC-MS: target compound content—99.9%, t134H170N14O34: m/z calculated for [M+H]+ 2520.2004, found: 2520.21.ESI-HRMS: for C10dSynthesis of compound 8d, 32 mg (35.9 µmol) of Docetaxel-alkyne 9, 7 mg (35.9 µmol) of sodium ascorbate, 3 mg (11.9 µmol) of copper sulfate pentahydrate in 10.6 mL of DMF/water mixture (3/1), followed by addition of 7 mg (23.9 µmol) EDTA was isolated individually using reverse phase column chromatography  64 mg (85% yield) of compound 10d as white powder.From 48 mg (29.9 µmol) of compound 1H NMR  δ, ppm: 8.82 , 8.69 , 8.51 , 7.92–7.99 , 7.80–7.92 , 7.78 , 7.65–7.75 , 7.58–7.65 , 7.28–7.41 , 7.20–7.28 , 7.01–7.20 , 6.44 , 5.67–5.79 , 5.36 , 5.31 , 4.97–5.08 , 4.87 , 4.50–4.57 , 4.32–4.45 , 4.17–4.31 , 3.92–4.12 , 3.59 , 3.09–3.22 , 2.89–3.09 , 2.78–2.89 , 2.54–2.68 , 2.41 , 2.10–2.36 , 1.77–2.10 , 1.54–1.74 , 1.47 , 1.24–1.41 , 1.06–1.24 , 0.98 , 0.94 .R = 9.49 min.HPLC-MS: target compound content—99.9%, t134H170N14O33: m/z calculated for [M+H]+ 2504.2055, found: 2504.21.ESI-HRMS: for C12a–dGeneral procedure for preparing monomodal conjugates 6a–d (1.1 eq.) and MMAE-alkyne  were dissolved in a mixture of DMF and water. The flask was filled with argon, then aqueous solutions of sodium ascorbate (1.2 eq.) and copper sulfate pentahydrate (0.4 eq.) were added. The reaction mixture was stirred for 18 h. Afterwards, EDTA (0.8 eq.) was added and stirred for three hours with access to oxygen in air. The solvent was removed under reduced pressure, then the dry residue was precipitated with acetonitrile and decanted. Then, the product was isolated individually using reverse phase column chromatography using acetonitrile–water mixture as eluent.Ligand 12aSynthesis of compound 6a, 89 mg (73.2 µmol) of compound 11, 17 mg (87.8 µmol) of sodium ascorbate, 6 mg (29.3 µmol) of copper sulfate pentahydrate in 13.5 mL DMF/water mixture (3/1), followed by addition of 17 mg (58.6 µmol) EDTA was isolated individually using reverse phase column chromatography  86 mg (49% yield) of compound 12a as white powder.From 104 mg (80.5 µmol) of compound 1H NMR  δ, ppm: 12.51 , 10.00 , 9.22 , 8.28 , 8.13 , 7.84–7.96 , 7.82 , 7.52–7.74 , 7.09–7.40 , 7.00–7.07 , 6.65 , 6.31 , 5.99 , 5.42 , 4.90–5.13 , 4.59–4.77 , 4.44–4.59 , 4.18–4.43 , 3.90–4.17 , 3.30 , 3.14–3.26 , 3.10 , 2.91–3.07 , 2.70–2.90 , 2.61–2.69 , 2.56 , 2.30–2.44 , 2.14–2.29 , 2.11 , 1.84–2.01 , 1.56–1.84 , 1.34–1.56 , 1.10–1.34 , 0.94–1.07 , 0.67–0.89 .13C NMR  δ, ppm: 174.50, 174.20, 173.77, 172.52, 172.17, 172.11, 171.71, 171.50, 171.34, 171.10, 170.62, 169.85, 168.75, 158.96, 157.29, 155.88, 146.46, 143.69, 141.22, 137.88, 133.41, 133.05, 130.62, 130.26, 130.05, 129.03, 128.18, 128.08, 127.83, 127.77, 127.19, 126.86, 126.68, 126.43, 126.29, 126.09, 124.97, 121.96, 118.81, 114.98, 114.84, 81.64, 74.82, 66.11, 63.29, 60.95, 58.18, 57.56, 57.14, 54.92, 53.18, 52.57, 52.15, 51.66, 50.28, 49.75, 49.18, 47.23, 46.86, 46.26, 43.77, 43.21, 38.71, 37.14, 36.97, 35.81, 35.06, 34.67, 32.28, 31.81, 31.57, 31.21, 30.79, 30.59, 30.47, 29.91, 29.84, 29.34, 29.10, 27.79, 27.54, 26.83, 26.65, 26.29, 25.43, 24.66, 24.37, 23.14, 22.52, 22.26, 19.28, 18.95, 18.77, 18.56, 18.40, 18.24, 15.91, 15.48, 15.33, 15.05, 10.32.R = 11.47 min.HPLC-MS: target compound content—99.9%, t120H177ClN22O27: m/z calculated for [M+2H]2+ 1197.64938, found: 1197.645.ESI-HRMS: for C12bSynthesis of compound 6b, 73 mg (59.5 µmol) of compound 11, 14 mg (71.4 µmol) of sodium ascorbate, 6 mg (23.8 µmol) of copper sulfate pentahydrate in 10.8 mL DMF/water mixture (3/1), followed by addition of 14 mg (47.6 µmol) EDTA was isolated individually using reverse phase column chromatography  60 mg (41% yield) of compound 12b as white powder.From 80 mg (65.5 µmol) of compound 1H NMR  δ, ppm: 12.52 , 9.99 , 9.20 , 8.24–8.37 , 8.11–8.15 , 7.84–7.96 , 7.82 , 7.59–7.70 , 7.51–7.59 , 7.48 , 7.08–7.35 , 7.03 , 6.65 , 6.29–6.33 , 6.00 , 5.41 , 4.95–5.14 , 4.62–4.73 , 4.23–4.53 , 3.38–4.23 , 3.08–3.26 , 2.78–3.08 , 2.70–2.78 , 2.60–2.69 , 2.52–2.60 , 2.15–2.42 , 2.11 , 1.84–2.04 , 1.63–1.84 , 1.33–1.58 , 1.11–1.33 , 0.89–1.08 , 0.65–0.89 .13C NMR  δ, ppm: 174.51, 174.22, 173.78, 172.37, 172.09, 171.71, 171.50, 171.35, 171.10, 168.74, 158.96, 157.28, 155.88, 146.45, 143.70, 138.03, 137.88, 131.57, 131.25, 130.05, 129.73, 129.03, 128.65, 128.19, 128.08, 127.83, 126.47, 121.97, 119.93, 114.98, 74.80, 60.95, 60.31, 57.18, 54.92, 54.15, 51.65, 46.86, 43.21, 38.70, 37.48, 36.99, 35.80, 34.67, 31.80, 30.48, 29.91, 29.02, 27.54, 26.65, 26.30, 25.43, 24.65, 24.36, 22.27, 19.28, 18.24, 15.49, 15.32, 10.31.R = 11.68 min.HPLC-MS: target compound content—99.9%, t120H177BrN22O27: m/z calculated for [M+2H]2+ 1219.62412, found: 1219.6244.ESI-HRMS: for C12cSynthesis of compound 6c, 93 mg (76.6 µmol) of compound 11, 18 mg (91.9 µmol) sodium ascorbate, 8 mg (30.6 µmol) copper sulfate pentahydrate in 13.5 mL DMF/water mixture (3/1), followed by the addition of 18 mg (61.3 µmol) EDTA was isolated individually using reverse phase column chromatography  101 mg (55% yield) of compound 12c as white powder.From 100 mg (84.2 µmol) of compound 1H NMR  δ, ppm: 12.62 , 9.99 , 9.22 , 8.24–8.37 , 8.10–8.16 , 7.84–7.96 , 7.82 , 7.54–7.66 , 7.10–7.35 , 7.03 , 6.64 , 6.23–6.40 , 6.00 , 5.41 , 4.91–5.13 , 4.73 , 4.18–4.66 , 4.03–4.18 , 3.89–4.03 , 3.13–3.27 , 2.91–3.10 , 2.79–2.91 , 2.54–2.79 , 2.13–2.39 , 2.11 , 1.84–2.01 , 1.34–1.84 , 1.10–1.34 , 0.93–1.08 , 0.64–0.90 .13C NMR  δ, ppm: 174.50, 174.21, 173.77, 172.53, 172.31, 172.10, 171.71, 171.51, 171.34, 171.10, 170.60, 169.91, 169.85, 168.74, 167.21, 158.96, 157.89, 157.28, 155.88, 146.45, 143.77, 143.69, 137.88, 130.05, 129.78, 129.47, 129.02, 128.19, 128.08, 127.83, 127.77, 127.39, 126.67, 126.47, 126.42, 126.28, 121.96, 118.95, 114.98, 89.66, 74.80, 60.95, 60.31, 58.68, 57.57, 57.17, 54.95, 54.14, 53.15, 52.57, 52.12, 51.65, 46.87, 40.44, 38.71, 37.02, 35.81, 34.68, 32.32, 31.78, 31.54, 31.22, 30.80, 30.48, 29.91, 29.84, 29.35, 29.12, 27.53, 26.65, 26.31, 25.43, 25.37, 24.66, 24.36, 23.14, 22.52, 22.25, 19.28, 18.98, 18.24, 15.49, 15.32, 15.05, 10.33.R = 11.32 min.HPLC-MS: target compound content—99.9%, t121H178N22O29: m/z calculated for [M+2H]2+ 1202.66378, found: 1202.664.ESI-HRMS: for C12dSynthesis of compound 6d, 47 mg (38.8 µmol) of compound 11, 9 mg (46.6 µmol) of sodium ascorbate, 4 mg (15.5 µmol) of copper sulfate pentahydrate in 9.5 mL DMF/water mixture (3/1), followed by addition of 9 mg (31.1 µmol) EDTA was isolated individually using reverse phase column chromatography  43 mg (45% yield) of compound 12d as white powder.From 50 mg (42.7 µmol) of compound 1H NMR  δ, ppm: 12.45 , 9.99 , 8.23–8.39 , 8.02–8.23 , 7.79–8.01 , 7.56–7.74 , 7.10–7.38 , 6.17–6.44 , 6.00 , 4.93–5.18 , 4.72 , 4.24–4.66 , 3.56 , 3.28–3.58 , 3.08–3.26 , 2.79–3.08 , 2.75 , 2.53–2.61 , 2.08–2.40 , 1.85–2.00 , 1.62–1.84 , 1.34–1.62 , 1.09–1.34 , 0.94–1.08 , 0.66–0.92 .13C NMR  δ, ppm: 174.55, 174.50, 174.21, 173.78, 172.54, 172.09, 171.75, 171.53, 171.33, 170.94, 168.74, 158.95, 157.28, 146.46, 143.70, 137.83, 129.78, 129.46, 129.37, 129.12, 129.01, 128.18, 128.08, 127.83, 127.77, 127.39, 126.76, 126.45, 121.98, 74.81, 57.14, 54.50, 52.60, 51.65, 46.87, 38.71, 35.83, 31.80, 30.55, 29.91, 29.12, 27.55, 26.65, 26.33, 25.44, 24.70, 23.14, 22.27, 19.28, 18.96, 18.24, 15.49, 15.32, 15.06, 10.32.R = 11.46 min.HPLC-MS: target compound content—99.9%, t121H178N22O28: m/z calculated for [M+2H]2+ 1194.66632, found: 1194.6669.ESI-HRMS: for C13a–dGeneral methodology for producing bimodal conjugates 12a–d (1 eq.) was dissolved in DMF to which NHS-ester of Abiraterone  and DIPEA (6 eq.) were added. The reaction mixture was stirred for 20 h, after which the solvent was removed under reduced pressure. The dry residue was precipitated with acetonitrile, the resulting precipitate was decanted and washed three times with acetonitrile. The solvent residue was removed under reduced pressure.Monoconjugate 13aSynthesis of compound 12a, 9 mg (17.0 µmol) of compound 7 and 15 µL (85.1 µmol) of DIPEA, 38 mg (95% yield) of compound 13a was obtained as white powder.From 34 mg (14.2 µmol) of compound 1H NMR  δ, ppm: 12.46 , 9.99 , 9.20 , 8.58 , 8.42 , 8.33 , 8.03–8.21 , 7.83–8.01 , 7.81 , 7.68–7.78 , 7.51–7.67 , 7.08–7.40 , 7.04 , 6.64 , 6.23–6.37 , 6.10 , 5.98 , 5.42 , 5.35 , 4.91–5.15 , 4.59–4.77 , 4.16–4.59 , 4.03–4.16 , 3.88–4.03 , 3.57 , 3.13–3.26 , 3.11 , 2.90–3.08 , 2.77–2.89 , 2.60–2.70 , 2.53–2.60 , 2.43 , 2.13–2.40 , 1.85–2.13 , 1.74–1.84 , 1.56–1.74 , 1.44–1.56 , 1.11–1.43 , 0.92–1.11 , 0.67–0.92 .13C NMR  δ, ppm: 174.50, 174.20, 173.77, 172.38, 172.31, 172.10, 171.79, 171.58, 171.48, 171.34, 171.09, 170.56, 169.90, 169.84, 168.75, 158.92, 157.27, 155.86, 151.01, 147.84, 147.20, 146.40, 143.69, 141.22, 140.81, 139.87, 137.86, 133.33, 133.05, 132.16, 130.59, 130.24, 130.00, 129.01, 128.17, 128.05, 127.94, 127.76, 127.21, 126.75, 126.42, 126.25, 126.08, 124.96, 123.43, 121.98, 121.92, 118.98, 114.98, 85.43, 74.81, 73.17, 60.94, 60.30, 58.67, 58.19, 57.59, 57.14, 56.99, 54.99, 54.17, 53.17, 52.88, 52.17, 51.68, 49.63, 49.18, 47.16, 46.84, 46.66, 46.27, 43.78, 43.22, 38.44, 37.71, 36.42, 36.31, 35.77, 34.67, 34.55, 32.29, 31.87, 31.54, 31.33, 30.96, 30.75, 30.57, 30.45, 29.95, 29.89, 29.36, 29.10, 28.91, 27.80, 27.60, 27.35, 26.84, 26.30, 25.41, 24.66, 24.36, 23.14, 22.91, 22.35, 20.40, 19.27, 18.93, 18.58, 18.24, 16.28, 15.87, 15.48, 15.30, 15.04, 10.43.R = 1.64 min.HPLC-MS: target compound content—99%, t148H210ClN23O30: m/z calculated for [M+2Na]2+ 1435.25435, found: 1435.2559.ESI-HRMS: for C13bSynthesis of compound 12b, 10 mg (17.2 µmol) of compound 7 and 16 µL (86.1 µmol) of DIPEA, 33 mg (80% yield) of compound 13b was obtained as white powder.From 35 mg (14.4 µmol) of compound 1H NMR  δ, ppm: 12.40 , 9.98 , 9.21 , 8.58 , 8.39–8.46 , 8.32 , 8.10–8.19 , 7.96–8.10, , 7.82–7.96, , 7.78–7.82 , 7.74 , 7.50–7.65 , 7.47 , 7.08–7.41 , 7.04 , 6.64 , 6.24–6.36 , 6.10 , 5.97 , 5.32–5.45 , 4.92–5.12 , 4.56–4.79 , 4.18–4.51 , 3.90–4.14 , 3.51–3.60 , 3.08–3.24 , 2.90–3.06 , 2.80–2.90 , 2.52–2.70 , 2.15–2.35 , 1.85–2.13 , 1.74–1.84 , 1.63–1.74 , 1.55–1.63 , 1.44–1.55 , 1.29–1.44 , 1.12–1.28 , 0.94–1.05 , 0.70–0.88 .13C NMR  δ, ppm: 174.53, 174.24, 173.81, 172.38, 172.11, 171.80, 171.60, 171.49, 171.35, 171.12, 170.57, 169.85, 168.76, 158.93, 157.28, 155.87, 151.00, 147.84, 147.19, 146.40, 143.69, 139.87, 137.85, 133.33, 132.14, 131.56, 131.24, 130.01, 129.73, 129.01, 128.66, 128.18, 128.06, 127.94, 127.83, 127.77, 126.74, 126.47, 126.27, 123.45, 121.99, 120.15, 119.93, 118.96, 114.99, 81.64, 74.80, 73.17, 60.95, 60.31, 57.59, 57.17, 56.99, 55.02, 54.17, 53.17, 52.89, 52.13, 51.69, 49.63, 46.83, 46.65, 46.28, 43.78, 43.23, 38.44, 37.71, 36.41, 36.31, 35.83, 34.66, 34.54, 31.80, 31.33, 30.96, 30.45, 29.89, 29.36, 29.10, 28.91, 27.74, 27.62, 27.35, 26.84, 26.32, 25.41, 24.73, 24.65, 24.36, 22.92, 22.36, 20.40, 19.27, 18.94, 18.55, 18.25, 16.28, 15.86, 15.65, 15.48, 15.31, 15.05, 10.32.R = 9.27 min.HPLC-MS: target compound content—99.9%, t148H210BrN23O30: m/z calculated for [M+2Na]2+ 1457.22909, found: 1457.2319.ESI-HRMS: for C13cSynthesis of compound 12c, 14 mg (25.0 µmol) of compound 7 and 22 µL (0.125 mmol) of DIPEA, 49 mg (83% yield) of compound 13c was obtained as white powder.From 50 mg (20.8 µmol) of compound 1H NMR  δ, ppm: 12.47 , 9.98 , 9.21 , 8.58 , 8.42 , 8.24–8.36 , 8.10–8.17 , 8.02–8.10  7.82–8.01 , 7.81 , 7.67–7.77 , 7.53–7.64 , 7.22–7.33 , 7.16–7.22 , 7.10–7.16 , 7.00–7.07 , 6.64 , 6.25–6.34 , 6.10 , 5.97 , 5.30–5.44 , 4.91–5.10 , 4.68–4.87 , 6.50–4.61 , 4.39–4.50 , 4.30–4.39 , 4.16–4.30 , 4.04–4.14 , 3.89–4.03 , 3.50–3.60 , 3.12–3.24 , 3.10 , 2.90–3.07 , 2.80–2.89 , 2.61–2.69 , 2.56 , 2.41–2.46 , 2.16–2.34 , 1.84–2.07 , 1.74–1.83 , 1.56–1.74 , 1.29–1.56 , 1.11–1.29 , 0.95–1.05 , 0.70–0.89 .13C NMR  δ, ppm: 174.55, 174.22, 173.79, 172.37, 172.31, 172.12, 171.79, 171.60, 171.49, 171.35, 171.11, 170.57, 169.84, 168.75, 167.22, 158.93, 157.28, 155.86, 151.01, 147.81, 147.16, 146.40, 143.76, 143.69, 139.86, 137.85, 133.30, 130.01, 129.77, 129.46, 129.01, 128.18, 128.06, 127.94, 127.82, 127.77, 127.39, 126.67, 126.47, 126.27, 121.98, 121.92, 118.98, 114.98, 85.42, 74.80, 73.17, 60.95, 60.31, 58.18, 57.60, 57.14, 56.98, 55.07, 53.18, 52.89, 52.15, 51.68, 49.62, 49.18, 46.83, 46.65, 46.27, 43.22, 38.43, 37.71, 36.41, 36.31, 35.86, 34.67, 34.53, 31.82, 31.50, 31.33, 30.96, 30.74, 30.46, 29.94, 29.88, 29.35, 28.90, 27.58, 27.34, 26.84, 26.23, 25.41, 24.65, 24.38, 23.14, 22.91, 22.37, 20.39, 19.27, 18.93, 18.41, 18.25, 16.27, 15.87, 15.65, 15.48, 15.31, 15.05, 10.32.R = 8.91 min.HPLC-MS: target compound content—99.9%, t149H211N23O32: m/z calculated for [M+2Na]2+ 1440.26875, found: 1440.2652.ESI-HRMS: for C13dSynthesis of compound 12d, 11 mg (19.1 µmol) of compound 7 and 17 µL (95.5 µmol) of DIPEA, 35 mg (78% yield) of compound 13d was obtained as white powder.From 38 mg (15.9 µmol) of compound 1H NMR  δ, ppm: 12.53 , 9.98 , 8.57 , 8.42 , 8.05–8.36 , 7.79–8.01 , 7.74 , 7.53–7.70 , 7.02–7.40 , 6.30 , 6.10 , 5.98 , 5.35–5.42 , 4.93–5.14 , 4.72 , 4.34–4.66 , 4.16–4.33 , 3.88–4.16 , 3.14–3.25 , 2.79–3.14 , 2.53–2.70 , 2.43 , 1.84–2.40 , 1.10–1.84 , 0.93–1.10 , 0.68–0.93 .13C NMR  δ, ppm: 174.53, 174.23, 173.80, 172.10, 171.80, 171.62, 171.35, 170.96, 170.57, 169.85, 168.74, 156.93, 150.99, 147.18, 146.40, 143.69, 139.86, 137.93, 137.82, 133.34, 129.76, 129.46, 129.08, 129.00, 128.18, 128.07, 127.83, 127.38, 126.68, 126.46, 123.45, 122.00, 121.92, 118.93, 81.75, 77.71, 74.80, 73.17, 60.95, 60.31, 57.59, 57.14, 56.98, 54.99, 54.67, 53.17, 52.92, 49.62, 46.84, 46.64, 46.26, 43.24, 37.70, 36.40, 36.31, 35.79, 34.54, 31.81, 31.54, 31.33, 30.96, 30.46, 29.87, 29.34, 29.12, 28.91, 27.63, 27.34, 26.85, 26.32, 25.42, 24.65, 24.37, 23.14 CH2 , 22.91, 20.40, 19.27, 18.93, 18.42, 18.25, 16.27, 15.48, 15.31, 15.05, 10.31.R = 8.39 min.HPLC-MS: target compound content—96%, t149H211N23O31: m/z calculated for [M+2Na]2+ 1432.27129, found: 1432.2719.ESI-HRMS: for C15Synthesis of a bimodal conjugate with the MMAE/Enzalutamide drug pair 12a and 24 mg  of compound 14 were dissolved in 20 mL of DMF. To the resulting solution, 38 μL  of DIPEA was added. The reaction mixture was stirred for 24 h, after which the solvent was removed under reduced pressure. Then, the product was precipitated with acetonitrile, decanted and the resulting precipitate was washed with acetonitrile. The target product was isolated individually using reverse phase column chromatography using a mixture of acetonitrile and water  as eluent. 20 mg (20% yield) of compound 15 was obtained as white powder.86 mg  of compound 1H NMR  δ, ppm: 12.49 , 9.99 , 9.20 , 8.35–8.62 , 8.28 , 8.02–8.20 , 7.70–7.98 , 7.49–7.69 , 6.94–7.45 , 6.63 , 6.29 , 5.97 , 5.29–5.47 , 5.03 , 4.72 , 4.18–4.65 , 3.87–4.15 , 3.50–3.80 , 3.08–3.26 , 2.75–3.07 , 2.62–2.74 , 2.03–2.36 , 1.90 , 1.63–1.83 , 1.09–1.61 , 0.99 , 0.64–0.89 .R = 9.20 min.HPLC-MS: target compound content—99.9%, t140H188ClF4N25O29S: m/z calculated for [M+2Na]2+ 1436.15673, found: 1436.1587.ESI-HRMS: for C2 vial, the cells were washed with PBS buffer and incubated for 5 min with 0.25% trypsin (1 mL). Trypsin was inactivated with complete growth medium (2 mL), washed with PBS, transferred 106 cells to a test tube, and 500 μL of lysis buffer  and 1× Proteinase Inhibition cocktail) was added. The suspension was incubated for 30 min on ice and sonicated  on ice to avoid overheating. The suspension was centrifuged for 10 min at 1000g at 4 °C, and the supernatant was used in further analysis.LNCaP cells were cultured in RPMI medium with 10% FBS , 1xGlutamax (Gibco) and 1x penicillin-streptomycin mixture . To suspend the cells, growth medium was removed from the 25 cm® Red reagent stock solution, 1.25 μL HRP stock solution, 8 μL L-glutamate oxidase, 2.5 μL L-glutamate pyruvate transaminase, 0.5 μL L-alanine, 483 μL 1× reaction buffer. Incubation was performed for 1 h at 37 °C. The fluorescence of resorufin produced by conjugated glutamate detection kit reactions was detected on a VICTORX5 multidetector plate  at an excitation length of 555 nm and detection at 580 nm. As a control for endogenous glutamate levels with replacement of the NAAG solution with water.The inhibition by PSMA ligands was analyzed using a non-radioactive protocol with detection of the glutamate released during the reaction. LNCaP cell line extract (10 μL) was mixed with 2 μL of the appropriate compound preparation. A series of dilutions of 2 nM-100 μM compounds was used for initial testing, with dilution steps of 3–5 times. To the resulting mixture, 1 μL of 100 μM NAAG solution was added. The mixture was incubated for 2 h at 37 °C. After incubation, the mixture was doubled with reaction buffer (13 μL) from the Amplex Red Glutamic Acid Kit , and the multi-component glutamate detection reaction mixture prepared according to the manufacturer’s protocol (26 μL) was added. Amplex Red stock solution: 5 μL Amplex2. Later, the culture medium from each well was removed and 20 μL of MTS reagent  were added to each well with 100 μL of new culture medium. After 4 h incubation at 37 °C in darkness, the absorbance of the solution was measured at 490 nm wavelength using Thermo Scientific Multiskan GO spectrometer. Cell viability was calculated as a percentage compared to control cells. The absorbance of MTS reagent in culture medium without cells was taken as zero. MTS assay revealed 100% cell death after incubation with 30% DMSO. Experiments were performed in triplicates. Data were analyzed using Prism 9—GraphPad version 9.2.0 software. p values < 0.05 were considered significant.The cytotoxicity of the investigated substances was tested using the MTS assay  with somAll animal procedures were conducted in strict adherence to the European Convention for the Protection of Vertebrate Animals Used for Experimental and other Scientific Purposes (ETS 123), Strasbourg, 1986. The procedures with animals were reviewed and approved by the bioethical committee of the National Medical Research Radiological Centre of the Ministry of Health of the Russian Federation, Protocol No. 23 from 22 June 2021.BALB/c nu/nu (nude) mice, males with body weights of 21–25 g (aged 8−10 weeks) were used. Animals were obtained from SPF-vivarium of the Center for Collective Use in Novosibirsk. All animals came with a veterinary passport and a certificate of quality.2 vials  in RPMI-1640 medium  with the addition of 2 mM L-glutamine  and 10% fetal calf serum  under standard conditions of cultivation (in a humidified atmosphere at 37 °C and 5% CO2). Cells of 6–10 passages were used to inoculate the animals. Cell suspension was prepared with a concentration of 5 × 106 cells in 0.05 mL of the 22Rv1 medium and in 0.1 mL of the PC-3 medium. 22Rv1 cells were inoculated into animals in Matrigel . Manipulations with Matrigel were performed on a refrigerated plate using precooled materials, tubes and instrumentation. For animal administration, 50 μL of the cell suspension (5 × 106 cells) was transferred to a chilled tube containing 50 μL of Matrigel; after mixing, the cellular material  was injected subcutaneously into the groin area of the animal. To obtain subcutaneous xenograft PC-3, a 5 × 106 suspension of tumor cells was inoculated subcutaneously into the inguinal cavity of male mice in a volume of 0.1 mL.Two cell lines were used: human prostate carcinoma 22Rv1 and prostate adenocarcinoma PC-3 (ATCC collection). Cells were cultured in 75 cmTissue samples obtained by the autopsy of animals on 14–21 days after cell inoculation were fixed in neutral buffered 10% formalin and encased in paraffin after a standard histological examination. Serial tissue sections with a 4 μm thickness were prepared. For histological analysis, the sections were stained with hematoxylin and eosin (H&E) according to the standard technique.Polyclonal rabbit antibodies Ab58779  were used to detect PSMA expression at a dilution of 1:100. Sections were stained using a common indirect immunoperoxidase assay technique. To demask the antigen, glasses with deparaffinized sections were incubated in 0.1 M sodium citrate buffer (pH 6.0) at 95 °C for 20 min. The system of secondary reagents included biotinylated polyclonal antibodies to rabbit immunoglobulins , streptavidin conjugate with horseradish peroxidase  and the chromogenic substrate Liquid DAB + Substrate Chromogen System . Non-specific rabbit immunoglobulins  were applied to control sections instead of primary antibodies. After the completion of the reaction, cells and sections were stained with hematoxylin and encapsulated in Canada balsam. Micropreparations were analyzed under an Olympus BX51 microscope equipped with an image documentation system.3. As a control substance, 0.9% sodium chloride solution was used. Experimental groups included five animals each. Conjugates 13a, 15, I and MMAE were formulated with Pluronic F-127 (the compound/Pluronic F-127 F weight ratio was 1:5). The mixture was dissolved in DMSO  and diluted with hemodesum (30% low-molecular-weight polyvinylpyrrolidone (Mw = 8000 ± 200) saline infusion solution). The presence of tumors and their sizes, as well as the body weights of the mice, were recorded every five days during the observation of the animals. The antitumor effect was assessed by comparing the tumor volumes in the experimental and control groups as well as the amount of tumor growth inhibition .To study the antitumor efficacy, conjugates were administered intravenously at a dose of 132.3 nM/kg to tumor-bearing mice three times at five-day intervals; administration was started 7−8 days after cell inoculation, and the tumor size was 70−90 mm2 inhalation chamber . All animals were euthanized either once the tumor volumes in the control group reached 2500 mm3 or due to the presence of necrosis or ulceration unrelated to tumor growth.In line with humane principles, animals were euthanized by placing mice in a COt-test or Mann–Whitney U-test were used to assess the reliability of differences between the groups, depending on the nature of the distribution of the trait in the groups.The data were statistically processed using the Statistica 8.0 software package . Group arithmetic mean (M) and standard error of the mean (m) as well as median (Me) were calculated for all quantitative data. Student’s 1, d2 and d3 are the three mutually perpendicular dimensions of the tumor.Tumor volume was calculated using Formula (1):k and Vo are average tumor volumes in the experimental and control groups, respectively.TGI was calculated according to Formula (2):6a–d), suitable for the creation of various bimodal conjugates targeting PCa cells. The introduction of a lysine residue into the structure of the linker peptide fragment did not lead to a significant decrease in the affinity to the protein target. We proposed a new bimodal conjugate preparation technique and used it to synthesize a series of bimodal conjugates based on ligands 6a–d with Docetaxel/Abiraterone drug pairs. In vitro cytotoxicity studies of these compounds showed the selective effect of these drugs on PCa cells with a range of PSMA expression levels. However, the cytotoxicity values were rather moderate. Subsequently, we performed the synthesis of four bimodal conjugates with the Abiraterone/MMAE drug pair and one conjugate with the Enzalutamide/MMAE drug pair. A further optimization of the synthetic route was carried out to obtain these five compounds. Subsequent in vitro studies showed that the obtained compounds show toxicity comparable to that of the Monomethyl Auristatin E conjugate previously described in the literature. Further in vivo studies in xenograft models of PCa demonstrated that the two bimodal conjugates 13a and 15 had efficacies comparable to the previously described conjugate with MMAE and were superior to the free MMAE. By using PSMA expressing and PSMA non-expressing models, we confirmed a further significant increase in the efficacy of such compounds on PSMA-expressing PCa cells.In this work, we synthesized four new PSMA ligands (